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https://issues.apache.org/jira/browse/YARN-291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13822052#comment-13822052
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Cindy Li commented on YARN-291:
-------------------------------

JunPing, 

I'm trying to find out where you handle different cases of commitTimeout, and 
getting to this in schedulerUtils.java:

      // TODO process resource over-commitment case (allocated containers
      // > total capacity) in different option by getting value of
      // overCommitTimeoutMillis.

What's your thought on this? Are you working on it? 

In our case, we would need to set overCommitTimeoutMills to be >0,  and the 
capacity(memory/vore) to be zero for node to be put into maintenance. What I 
would expect is:
#1. The scheduler stops scheduling new application attempts to the node
#2. Clean up containers on that node after overCommitTimeoutMills. 

>From my understanding, #1 is done once the capacity is set to 0, but what do 
>you plan to put there for #2? YARN-999 seems not solving #2.



> [Umbrella] Dynamic resource configuration
> -----------------------------------------
>
>                 Key: YARN-291
>                 URL: https://issues.apache.org/jira/browse/YARN-291
>             Project: Hadoop YARN
>          Issue Type: New Feature
>          Components: nodemanager, scheduler
>            Reporter: Junping Du
>            Assignee: Junping Du
>              Labels: features
>         Attachments: Elastic Resources for YARN-v0.2.pdf, 
> YARN-291-AddClientRMProtocolToSetNodeResource-03.patch, 
> YARN-291-CoreAndAdmin.patch, YARN-291-JMXInterfaceOnNM-02.patch, 
> YARN-291-OnlyUpdateWhenResourceChange-01-fix.patch, 
> YARN-291-YARNClientCommandline-04.patch, YARN-291-all-v1.patch, 
> YARN-291-core-HeartBeatAndScheduler-01.patch
>
>
> The current Hadoop YARN resource management logic assumes per node resource 
> is static during the lifetime of the NM process. Allowing run-time 
> configuration on per node resource will give us finer granularity of resource 
> elasticity. This allows Hadoop workloads to coexist with other workloads on 
> the same hardware efficiently, whether or not the environment is virtualized. 
> More background and design details can be found in attached proposal.



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